Metabolic analysis of acute appendicitis by using system biology approach.

Aim
Introducing possible suitable compound as diagnostic agent in appendicitis is aim of this investigation.


Background
Appendicitis diagnosis is a difficult step in treatment of disease due to complex abdominal pain signal which may be refer to the non-appendicitis pain.


Methods
Gene expression profiles of children with non-preforated appendicitis in comparison with the samples with non- appendicitis abdominal pain are analysis via protein - protein interaction (PPI) and the critical compounds are introduced by STITCH.


Results
Ten compounds including including MgATP, glycerol, MgADP, calcium ions, chloride, magnesium, phosphate, sulphate, acetate, and sodium are introduced as possible biomarker panel to differentiate appendicitis from the other abdominal pains.


Conclusion
A laboratory method such as flame photometry based on metal detection for diagnosis of appendicitis is possible, however more investigations are required.


Introduction
1 Appendicitis as one of the poorly recognized abdominal pain is common in all ages worldly (1). The annual incident of this emergency condition is 1.1 cases per 1000 individuals (2) with highest rate of abdominal surgery in children (3). The diagnosis, screening and treatment for this condition is remained complicated (1) due to heterogeneity of clinical manifestation and lack of potential biomarkers (4). What is more, one of the drawbacks of current clinical diagnostic methods is the usage of tomography that imposes notable radiation contact (5). Additionally, there are some reports regarding misdiagnosis of appendicitis that resulted in removing healthy appendix with rate of 17% to 28% outside the U.S. and Western Europe (5). Thus, the requirement for detecting putative biomarkers in this regard concluded in different molecular investigations (6). These studies could introduce elements that possibly upgrading clinical evaluations (4,7). In view of this fact, there are some high throughput studies including genomics, proteomics, and metabolomics (4,8,9). In addition, to gain more reliable and accurate candidates, one way is to study these suggested biomarkers by system biology in terms of interaction values. Protein-protein interaction (PPI) network analysis could be beneficial in adding more knowledge about the identified biomarkers and their corresponding biological processes and filtering the most promising ones for advancing clinical assessments (10, ORIGINAL ARTICLE 11). In a way that, the PPI are key assets of accelerating a biological response to a certain condition of a cell. Modifications in these interactions could change the vital characteristic of that cell. In another world, abnormal conditions such as a disease state could occur. The participations of these communicating proteins are critical in the matter of dysregulations. In fact, any significant expression alteration in these agents may be responsible for abnormal interactome and ultimately for the disease condition (12). Consequently, for the analysis and better understanding of the mechanisms underlying Appendicitis, PPI network study could be favorable via transcriptome profile examinations.

Methods
Gene expression profiles of 4 acute appendicitis and 17 inguinal hernia (as controls); GSE83091/GPL10558, were retrieved from GEO. The samples were matched via box plot analysis and the comparable ones were selected four further analysis. Numbers of 250 top significant DEGs were considered and the significant and characterized ones were selected to analyze via PPI network analysis. After adding 100 relevant proteins or compounds, the queries were included in a interacted unit by STITCH a plugin of Cytoscape software (13). The top 10% of nodes based on degree value were determined as hubs. All interacted compounds were selected as relevant compounds which are involved in appendicitis. The top compounds which were common with top hubs were identified as critical compounds related to appendicitis. P-value less than 0.05 and fold change more than 2 and less than 0.5 were regarded.

Results
Gene expression profiles of 4 acute appendicitis patients and 17 inguinal hernia samples were compared via box plot analysis. The samples were not matched statistically ( Figure  1) because profiles are not median centered. As it is shown in figure 2, the proper samples were selected for more analysis. Among top 250 significant DEGs, 146 Characterized ones with fold change; more than 2 and less than 0.5 were determined to include in network analysis. The 146 selected DEGs plus 100 relevant individual genes or compounds were organized by STITCH application of Cytoscape software as network of appendicitis. The network including 226 nodes was constructed (see figure 3).
As it is appeared 20 queried DEGs were not recognized by STITCH. After network analysis, about 10% (20 nodes) of top nodes based on degree value were identified as hubs. As it is shown in the table 1, the introduced hubs are combination of proteins and compounds. All compounds content of network including 40 nodes are presented in the table 2. As it is appeared in the table 1, the top 9 hubs are compounds and are similar as top compounds in the table 2.

Discussion
Network analysis of diseases is an attractable field which used to biomarker discovery and also gene screening of disorders (14)(15)(16). Suitable sample selection is an important step in research. As it was shown in the figures 1 and 2, boxplot analysis is a useful method to match samples (17). PPI network in figure 3 contains 226 proteins and compound that are involved in appendicitis. Main aim in this study is finding critical compounds that are involved in appendicitis. Network analysis led to introduce 20 hub nodes for appendicitis network (see table 1). Hub nodes include 6 protein and 14 compounds. All compounds of PPI network are 43 individual that three of them are isolated and the interacted ones (see table 1) are 40 individuals. Surprisingly 9 compounds including MgATP, glycerol, MgADP, calcium ions, chloride, magnesium, phosphate, sulphate, and acetate play role as top hub nodes, therefore they can be considered as key elements of network (18). As it is depicted in table 1, the key elements are top nodes based on betweenness centrality and closeness centrality values, however phosphate is an exception regarding betweenness centrality. Sodium the other hubs which is ranked in row 15 in table 1 and row 11 in table 2 can be ranked in row 6 in table 2 based on betweenness centrality. Since As they are reported procalcitonin concentration in serum of NPAC group increases and acetate concentration level decreases (20). Calcitonin is hormone of thyroid gland and is responsible for decrement of calcium ion in blood. Mg up-regulates calcitonin production, therefore plays a central role in calcium ion in blood (21). Role of calcium in contraction of smooth muscles is known in details (22). Intra-abdominal muscle contraction is reported in appendicitis (23). As it is shown in the table 2, Calcium, magnesium, acetate are the three elements of central compounds related to appendicitis. MgATP and MgADP are the other two important compounds which are composites including Mg. Today it is well-known that calcium regulation is correlated to phosphate homeostasis (24). An investigation showed that there is correlation between appendicitis and oxidative stresses. Since glycerol increases oxidation reaction (25) it can be related indirectly to appendicitis (26). It seems that appendicitis is correlated mainly to ion compounds especially calcium. It is a logical expectation that calcium level of blood be altered significantly. The finding s are in agreement with this point that calcium and the other agents that are involved in calcium concentration regulation are the important compounds which are possible biomarkers for acute appendicitis. As it is appeared in the table 2, concentration alteration of other metal ions such as sodium, zinc, and potassium are related to appendicitis. Since flame photometry is a simple method for detection metal concentration it can be concluded that differentiation between appendicitis pain and the other abdominal pains is possible. However, more investigations are needed to validate this finding. Based on our findings a ten member panel of compounds including calcium play critical role in differentiation of appendicitis of the other nonappendicitis abdominal pains. Therefore, it is possible to introduce a simple laboratory method for diagnosis appendicitis. In this regard more investigations to validate the findings are required.